similar to: wilcox.test returning 'NA' p-value

Hello, I'm trying to compare the allozyme data from two taxa. I have several columns of data (19 loci) for each species. I want to do a Mann-Whitney U-test or the wilcox.test (two sample Wilcoxon). When I try to run my code (the first two columns are 1:name of the species, 2:name of individual) I get the error message: "Error in wilcox.test.default(CaScSc, CaScCo, alternative

Dear all, I want to compare the efficiency of 2 methods in extracting proteins from algal samples. I collected 6 independant algal samples and I extracted 3 by the method 1 and 3 others by the method 2. So I have 2 groups of 3 samples, that are not paired. I would like to know if the results obtained by these 2 methods are significantly different, I hope method 2 to be more efficient than method

Hi, Could anyone provide the formula of the statistics which the wilcox.test used for the two-sample rank-sum test? I got some statistics of 0 values, but it is impossible to have 0 "rank-sum". Does the function use the Mann-Whitney U test statistics? Thanks. Ting-Yuan Liu

I'm working on a quick tutorial for my students, and was planning on using Mann-Whitney U as one of the tests. I have the following (fake) data grade <- c("MVG", "VG", "VG", "G", "MVG", "G", "VG", "G", "VG") sex <- c( "male", "male", "female", "male",

Hi, I believe I have significantly improved [dpq]wilcox functions by implementing Harding's algorithm: Harding, E.F. (1984): An Efficient, Minimal-storage Procedure for Calculating the Mann-Whitney U, Generalized U and Similar Distributions, App. Statist., 33, 1-6 Results on my computer show (against R-2.9.1): > system.time( dwilcox( 800, 800, 80) ) user system elapsed 0.240

Hi, Could someone please tell me how to perform a Mann-Whitney U test on a dataset with 2 groups where one group has more data values than another? I have split up my 2 groups into 2 columns in my .txt file i'm using with R. Here is the code i have so far... group1 <- c(LeafArea2) group2 <- c(LeafArea1) wilcox.test(group1, group2) This code works for datasets with the same number

I am new to R and have two scripts written slightly different but should to relatively the same thing but my lack of experience with the program I can not figure out the what I need to do to correct it. The first script gives me a consistent mean fold change values with every run but can generate negative p values for some. For the second version of the script, the fold changes seem to be very

does anybody know why there are the two warnings in the example above? Regards Knut > day_4 [1] 540 1 1 1 1 1 1 300 720 480 > day_1 [1] 438 343 1 475 1 562 500 435 1045 890 > is.vector (day_1) [1] TRUE > is.vector (day_4) [1] TRUE > wilcox.test(day_4 ,day_1,paired=TRUE,alternative="two.sided",exact=TRUE,conf.int=TRUE) Wilcoxon

Good day all, My first posting to this list. It looked like the best place to post this question. When running the wilcox.test(), I noticed that the output values change if you change the ordering of the levels (example below which includes a t.test for comparison). I think this has something to do with the change in ranking order, but this doesn't make much sense as I would expect the

Hi all, I have being using wilcox.test to test for differences between 2 independent samples. I had understood the difference in location to be conventionally the difference in the sample medians however this is not the case when implemented in R. I have tied ranks and therefore non-exact p-value and confidence intervals are calculated due to the normal approximation. But what exactly is this

Dear All, 1. why did the problem happen? 2. How to solve it? -- Best wishes, Zhijiang Wang -------------------------------------------- PHD Student Room 212, Science buliding, The International WIC Institute, College of Computer Science and Technology, Beijing University of Technology, Beijing, China.

Dear Sir, I am comparing two samples using wilcox.test in R. Literature appears to describe mann whitney u test as the most appropriate test to use on my data. is the wilcox.test function equivalent to mann-whitney u? Is there a way to gain the U-value as apposed to the W-value in R? Thank you

Given this example #start code a<-c(0,70,50,100,70,650,1300,6900,1780,4930,1120,700,190,940, 760,100,300,36270,5610,249680,1760,4040,164890,17230,75140,1870,22380,5890,2430) b<-c(0,0,10,30,50,440,1000,140,70,90,60,60,20,90,180,30,90, 3220,490,20790,290,740,5350,940,3910,0,640,850,260) wilcox.test(a, b, paired=FALSE) #sum of rank for first sample sum.rank.a <-

Dear r-helpers, I want to test groups of samples for significant differences. Question: Does Group1 differ significantly from group2. This is a question to be answered by mann-whitney-u-test. I know that I can use wilcox.test with 2 samples. My problem: How can r perform the test automatically if there are more than 2 groups in my data frame. Test group1 vs. 2, 1 vs. 3, 1 vs. 4, etc. This is

Hello everyone, I'm having some trouble interpreting the results of a Wilcoxon (Mann-Whitney U) test. Hope you can help. This is the R script that I am running: a <- c(1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 2, 1, 5, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 3, 1, 1) b <- c(1, 2, 1, 1, 2, 3, 2, 2, 1, 2, 1, 1, 1, 2) wilcox.test(a, b, alternative="t", mu=0, exact=FALSE, paired=FALSE) #1st

Hello List, I'm trying to prepare some lecture notes on non parametric methods, and I can't manually reproduce the results of the wilcox.test function for ordinal data. The data I'm using are from David Howell's website, available here http://www.uvm.edu/~dhowell/StatPages/More_Stuff/OrdinalChisq/OrdinalChiSq.html If I run the wilcox.test function on the data I get a p-value of

Dear list, Let's say I have data a=c(37.961,38.214,57.68) b=c(77.56,61.875,67.683) wilcox.test(a,b) the wilcoxon test only gives me a p value with one decimal place. Is this normal? Thanks. Jun [[alternative HTML version deleted]]

Hi all, The Kruskal-Wallis test is a generalization of the two-sample Mann-Whitney test to *k* samples. That being the case, the Kruskal-Wallis test with *k*=2 should give an identical p-value to the Mann-Whitney test, should it not? x1<-c(1:5) x2<-c(6,8,9,11) a<-wilcox.test(x1,x2,paired=FALSE) b<-kruskal.test(list(x1,x2),paired=FALSE) a$p.value [1] 0.01587302 b$p.value [1]

Hi, I know that I can perform a Mann-Whitney U test with wilcox.test(x,y) But instead of an U-value I get a W-Value. Is it possible to change this?

I have a stupid question on how to get the real p-values for wilcox.test and correlation. the minmun can be reached is 2.2E-16 using the R version 2.6.2. I do not think it is the R version causing this but other issues. Any help is highly appreciated. Charles -- View this message in context: http://www.nabble.com/minmun-p-value-for-wilcox.test-and-correlation-tp23637568p23637568.html Sent